Delete app.py

app.py

@@ -1,41 +0,0 @@
-import gradio as gr
-from PIL import Image
-import random
-
-def dummy_deepfake_detector(image: Image.Image, prompt: str) -> tuple[str, Image.Image, str]:
-    """
-    Simulates a deepfake detector. Replace this logic with your real model.
-    """
-    # Dummy logic: randomly decide real or fake
-    prediction = random.choice(["Real", "Fake"])
-    score = 1 if prediction == "Real" else 0  # Leaderboard dummy score
-    return f"Prediction: {prediction}", image, f"You: {score} point{'s' if score != 1 else ''}"
-
-with gr.Blocks() as demo:
-    gr.Markdown("## Fool the Deepfake Detector")
-    gr.Markdown("Upload an image and fool the deepfake detection model. Give it a try!")
-
-    with gr.Row():
-        prompt_input = gr.Textbox(
-            label="Suggested prompt",
-            placeholder="e.g., A portrait photograph of Barack Obama delivering a speech...",
-            value="A portrait photograph of Barack Obama delivering a speech, with the United States flag in the background"
-        )
-
-    with gr.Row():
-        image_input = gr.Image(type="pil", label="", tool=None)
-        submit_btn = gr.Button("Upload")
-
-    with gr.Row():
-        prediction_output = gr.Text(label="Result")
-        image_output = gr.Image(label="", show_label=False)
-    
-    leaderboard = gr.Text(label="Leaderboard")
-
-    submit_btn.click(fn=dummy_deepfake_detector, 
-                     inputs=[image_input, prompt_input],
-                     outputs=[prediction_output, image_output, leaderboard])
-
-if __name__ == "__main__":
-    demo.launch()
-